Deep Learning

The Most Advanced Optimization Solution for Deep Learning

Deep neural networks are highly effective at solving problems across a wide range of use-cases, from understanding images to interpreting language to automatically recommending similar products. Tuning the hyperparameters of these models is crucial for their success, but is difficult because of their large number of hyperparameters and long training times.

SigOpt’s optimization solution enables deep learning engineers to effectively tune their models and keep track of important metadata during the iterative model development process.

Track and Analyze Experiments

Experiment reproducibility is one of the great problems in deep learning. As modelers explore new datasets, new architectures, and new training techniques, it is important to track the exact hyperparameters (and other settings) that led to certain results. Our solution includes an Experiment Insights dashboard to ensure that every single model that is trained and experiment that is run is tracked and available for analysis.